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7ee9f86
decouple agents to keep them working over time by duplicating a bit o…
nidup Mar 16, 2018
be5f2b8
re-organize doc
nidup Mar 16, 2018
fa1bcba
setup multi reinforcement agent
nidup Mar 16, 2018
561d59a
re-organize orders for multi reinforcement agent
nidup Mar 18, 2018
72eb42a
scout enemy's base the sooner as possible
nidup Mar 18, 2018
42fbb6a
add episode step in game results
nidup Mar 18, 2018
cd01ffa
split multi reinforcement commanders into modules
nidup Mar 18, 2018
a772422
re-work last step learning for attack commander
nidup Mar 18, 2018
1cd5984
remove step from commander's order function
nidup Mar 18, 2018
ff9588e
add qlearning build orders commander
nidup Mar 18, 2018
19bb6b6
build order training + build hellion & medivac
nidup Mar 19, 2018
63a7a8c
add build orders per enemy's race report
nidup Mar 19, 2018
65087da
add selecting build orders per race variant
nidup Mar 19, 2018
5a28da0
split attack and training qlearning commanders
nidup Mar 19, 2018
c19489e
simplified train units QLearning linked to BO capabilities
nidup Mar 20, 2018
7f71be2
extract training actions set
nidup Mar 20, 2018
60514e5
remove no action from training QLearning action sets
nidup Mar 20, 2018
9a3afca
add qlearning attack order
nidup Mar 20, 2018
d926a91
change commander attack reward system (based on destroyed building)
nidup Mar 21, 2018
d4d11ff
add 4 brains QLearning variant
nidup Mar 21, 2018
26b58cd
introduce goal commander
nidup Mar 23, 2018
3d07e1e
extract goals from commander
nidup Mar 24, 2018
72f3a77
be able to build 6 extra supply depots
nidup Mar 24, 2018
f7b6cb5
add a minimap analyser
nidup Mar 24, 2018
347b487
add a seek and detroy attack order
nidup Mar 24, 2018
1608cfc
improve attack commander implementation
nidup Mar 25, 2018
a402639
fix late game army freezing when no more minerals
nidup Mar 25, 2018
09ddca3
improve late game army moves
nidup Mar 26, 2018
5ff3e7c
improve late game attacking single units
nidup Mar 26, 2018
9332da7
add 4 quadrants attack variant
nidup Mar 27, 2018
a99cb81
add squad training qlearning variant + decouple
nidup Mar 28, 2018
60bf4d9
detect enemy's units
nidup Mar 29, 2018
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6 changes: 3 additions & 3 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -27,7 +27,7 @@ It has been slightly fine-tuned to be trained faster and win more games against

**Against [very-easy built-in AI](https://github.com/deepmind/pysc2/blob/master/pysc2/env/sc2_env.py#L51)**

![Image of ReinforcementMarineAgent 3](doc/ReinforcementMarineAgent_enemyb1.png)
![Image of ReinforcementMarineAgent 3](doc/ReinforcementMarineAgent/enemyb1.png)

Hybrid Reinforcement Attack Agent (Machine Learning - Generation 2)
-------------------------------------------------------------------
Expand All @@ -39,7 +39,7 @@ The build order and actions are enriched to train marines & marauders.

**Against [easy built-in AI](https://github.com/deepmind/pysc2/blob/master/pysc2/env/sc2_env.py#L51)**

![Image of HybridAttackReinforcementAgent 20](doc/HybridAttackReinforcementAgent_3_rax_rush-easy6.png)
![Image of HybridAttackReinforcementAgent 20](doc/HybridAttackReinforcementAgent/3_rax_rush-easy6.png)

```
Results on the 100 last games:
Expand Down Expand Up @@ -71,5 +71,5 @@ $ python3.6 generate_report.py --agent-name nidup.pysc2.agents.ReinforcementMari

Query the game results:
```
$ python3.6 generate_report.py --agent-name nidup.pysc2.agents.ReinforcementMarineAgent --filter win
$ python3.6 query_results.py --agent-name nidup.pysc2.agents.ReinforcementMarineAgent --filter win
```
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Binary file added doc/MultiReinforcementAgent/sequential.png
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